Immobilization of Candida rugosa Lipase on Magnetic Biosilica Particles: Hydrolysis and Transesterification Studies

Biodiesel is a renewable fuel used mainly in diesel engines. At the present time, biodiesel is largely produced by acid or alkali transesterification reactions. A hot spring water algae isolate “Kamptonema formosum” was cultivated at three different temperatures, and the algae oil was extracted using chloroform and methanol (v/v, 1/1 ratio) as the solvent. The maximum amount of algal biomass (1.86 g/L) was obtained at 25°C, and the extracted oil was found to be 48.7% of the total dry biomass. Diatomic earth particles (Biosilica) were magnetized via thermal co-precipitation reaction, and then it was grafted with polydopamine (MBioSi@PDA). The lipase was covalently immobilized on the surface of the MBioSi@PDA via Schiff’s base reaction. The immobilization conditions were optimized and 3.0 mg/mL as the initial lipase concentration in the immobilization medium was found to be the most favorable. At this lipase concentration, the amount of the immobilized lipase on the MBioSi@PDA particles and immobilization yield were found to be 81.9 mg/g and 67.9%, respectively. The MBioSi@PDA@lipase particles were used for conversion of K. formosum oil into biodiesel, and the conversion yield was found as 91.2% under optimum conditions. The fatty acid methyl ester (FAME) compositions of the alga oil were identified using a gas chromatography-mass spectrometry (GC-MS). K. formosum oil mainly composed of the required fatty acids (i.e., 16 and 18 carbon long-saturated and unsaturated fatty acids) for biodiesel synthesis, and these were advantageous for synthesis of biodiesel from the algal oil. © 2021, The Korean Society for Biotechnology and Bioengineering and Springer

Biosorption of Cr(VI) by free and immobilized Pediastrum boryanum biomass: equilibrium, kinetic, and thermodynamic studies

15th International Symposium on Toxicity Assessment (ISTA) -- JUL 03-08, 2011 -- City Univ Hong Kong, Hong Kong, PEOPLES R CHINAWOS: 000306790200053PubMed ID: 22374187The biosorption of Cr(VI) from aqueous solution has been studied using free and immobilized Pediastrum boryanum cells in a batch system. The algal cells were immobilized in alginate and alginate-gelatin beads via entrapment, and their algal cell free counterparts were used as control systems during biosorption studies of Cr(VI). The changes in the functional groups of the biosorbents formulations were confirmed by Fourier transform infrared spectra. The effect of pH, equilibrium time, initial concentration of metal ions, and temperature on the biosorption of Cr(VI) ion was investigated. The maximum Cr(VI) biosorption capacities were found to be 17.3, 6.73, 14.0, 23.8, and 29.6 mg/g for the free algal cells, and alginate, alginate-gelatin, alginate-cells, and alginate-gelatin-cells at pH 2.0, which are corresponding to an initial Cr(VI) concentration of 400 mg/L. The biosorption of Cr(VI) on all the tested biosorbents (P. boryanum cells, alginate, alginate-gelatin, and alginate-cells, alginate-gelatin-cells) followed Langmuir adsorption isotherm model. The thermodynamic studies indicated that the biosorption process was spontaneous and endothermic in nature under studied conditions. For all the tested biosorbents, biosorption kinetic was best described by the pseudo-second-order model.PROCORE-France/Hong Kong Joint Res Scheme, Croucher Fdn, KC Wong Educ Fd

Identification of phantom movements with an ensemble learning approach

Phantom limb pain after amputation is a debilitating condition that negatively affects activities of daily life and the quality of life of amputees. Most amputees are able to control the movement of the missing limb, which is called the phantom limb movement. Recognition of these movements is crucial for both technology-based amputee rehabilitation and prosthetic control. The aim of the current study is to classify and recognize the phantom movements in four different amputation levels of the upper and lower extremities. In the current study, we utilized ensemble learning algorithms for the recognition and classification of phantom movements of the different amputation levels of the upper and lower extremity. In this context, sEMG signals obtained from 38 amputees and 25 healthy individuals were collected and the dataset was created. Studies of processing sEMG signals in amputees are rather limited, and studies are generally on the classification of upper extremity and hand movements. Our study demonstrated that the ensemble learning-based models resulted in higher accuracy in the detection of phantom movements. The ensemble learning-based approaches outperformed the SVM, Decision tree, and kNN methods. The accuracy of the movement pattern recognition in healthy people was up to 96.33%, this was at most 79.16% in amputees. 2022 The Author(s)This study is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under grant no. EEEAG-117E579. The data that support the findings of this study are available on request from the principle investigator of the project EEEAG-117E579, Akhan Akbulut, PhD. The data are not publicly available due to the confidential information that could compromise the privacy of research participants. Open Access funding provided by the Qatar National Library.Scopus2-s2.0-8513934593

Black sea aquaculture: Legacy, challenges & future opportunities

Responsible aquaculture, the farming of aquatic organisms, is a sustainable strategic sector for land and coastal communities. It significantly contributes to food security and enhancement of economic development; it provides employment opportunities and often contributes to the ecological services provided by the environment. According to the Food and Agriculture Organization of the United Nations (FAO), the contribution of aquaculture to the global food security is widely demonstrated by an astounding industry growth of 7.5% per year since 1970. In 2018, aquaculture reached the all-time highest production of 114.5 million tonnes in live weight with a total farm gate sale value of USD 263.6 billion. This makes aquaculture a key player within the Blue Growth concept and a strong contributor to some of its key Sustainable Development Goals (SDG). This is particularly true in geographical areas where dependence of local economies on fishery products is high, and yet access to sustainable landings is hampered by ecological barriers. One such area is represented by the Black Sea basin. Whilst the Black Sea annual capture fishery production has varied considerably since 1990 and its current landings are significant, growing attention is currently given to boost aquaculture development along the Black Sea bordering countries, with marine aquaculture being considered as an important contributor to the total fisheries production. Nonetheless, aquaculture development in this region is not homogenous and its development has, so far, been limited by environmental, economic, social, and more generally governance issues. This paper, for the first time, attempts to provide a comprehensive fresh outlook of the aquaculture sector in the Black Sea, stressing the importance of regional cooperation as an essential pillar to support the sustainable development of the industry. The paper addresses aquaculture in the Black Sea from different perspectives: it outlines the key characteristics of the Black Sea environment; it discusses the most common farmed aquatic species and the potential for new ones; it frames the national approaches to aquaculture development, sharing information about success stories, while shedding light on the main challenges and priorities ahead. This collective endeavour will represent a helpful contribution to Black Sea riparian countries to answer the many questions they have, and expectations they hold from the aquaculture sector.Additional co-authors: Dilek Fidan, Linda Fourdain, Marco Frederiksen, Archil Guchmanidze, Housam Hamza, Jessica Harvey, Magda Nenciu, Galin Nikolov, Victor Niţă, Muhammed Doğan Özdemir, Elitsa Petrova-Pavlova, Gabriel Popescu, Ferit Rad, Şafak Seyhaneyildiz Can, John A. Theodorou, Behnan Thomas, Nicolò Tonachella, Ekaterina Tribilustova, Irina Yakhontova, Ahmet Faruk Yesilsu, Güzel Yücel-Gie

The Bostrichidae of the Maltese Islands (Coleoptera)

The Bostrichidae of the Maltese Islands are reviewed. Ten species are recorded with certainty from this Archipelago, of which 6 namely, Trogoxylon impressum (Comolli, 1837), Amphicerus bimaculatus (A.G. Olivier, 1790), Heterobostrychus aequalis (Waterhouse, 1884), Sinoxylon unidentatum (Fabricius, 1801), Xyloperthella picea (A.G. Olivier, 1790) and Apate monachus Fabricius, 1775 are recorded for the first time. Two of the mentioned species (H. aequalis and S. unidentatum) are alien and recorded only on the basis of single captures and the possible establishment of these species is discussed. Earlier records of Scobicia pustulata (Fabricius, 1801) from Malta are incorrect and should be attributed to S. chevrieri (A. Villa & J.B. Villa, 1835). A zoogeographical analysis and an updated checklist of the 12 species of Bostrichidae recorded from the Maltese Islands and neighbouring Sicilian islands (Pantelleria, Linosa and Lampedusa) are also provided. Rhizopertha dominica (Fabricius, 1792) form granulipennis Lesne in Beeson & Bhatia, 1937 from Uttarakhand (northern India) was overlooked by almost all subsequent authors. Its history is summarized and the following new synonymy is established: Rhizopertha dominica (Fabricius, 1792) form granulipennis Lesne in Beeson & Bhatia, 1937 = Rhyzopertha dominica (Fabricius, 1792), syn. n. Finally, records of Amphicerus bimaculatus from Azerbaijan, of Bostrichus capucinus (Linnaeus, 1758) from Jordan and Syria, of Scobicia chevrieri from Jordan and Italy, of Xyloperthella picea from Italy, and of Apate monachus from Corsica (France) and Italy, are also provided.peer-reviewe

Geodesics and killing vector fields in a tangent bundle

The main purpose of this paper is to study geodesics and Killing vector fields in a tangent bundle with respect to the synectic lift s∇ of an affine connectio

SUPPORT VECTOR MACHINES COMBINED WITH FEATURE SELECTION FOR DIABETES DIAGNOSIS

Clinical Decision Support Systems (CDSS) are used as a service software which provides huge support to clinical decision making process where the main properties of a patient are matched to a tangible clinical knowledge. Within this gathered important information about patients, the medical decisions can be made more accurately. In this paper we present a CDSS that uses four physiological parameters of patients such as Pre-prandial Blood Glucose, Postprandial Blood Glucose, Hemoglobin A1C (HbA(1c)) and Glucose in Urine to produce a prediction about the possibility of being diabetic. According to collected reference data provided from hospitals, the disease can be predicted by comparing the input data of patients. If the system cannot procure a prediction about patients' status with these parameters, then the second phase which uses soft computing techniques is put into process with requesting additional data about patients. Our conducted experiments show that the diagnosis can be established in a breeze by getting the patients information with % 80 accuracy. Support Vector Machines were applied to achieve maximum success rate with nine different physiological parameters such as; Pregnancy, glucose, blood pressure, skin fold, insulin, Hemoglobin A1C, body mass index, family tree and age. Four different Kernel Functions are implemented in case studies and classification process is optimized by reducing attributes with feature selection algorithms. This represents an improvement in classification of CDSS, while reducing computational complexity

Smart Wearable Patient Tracking Systems

Nowadays Smart Wearable Systems (SWS) subject, emerges as one of the most popular research topic. Becouse of being comprimised from multiple disciplines, this area is favored by researchers of different areas. Devices of SWS are designed to measure physiological parameters for illnesses, chronic diseases, daily activity monitoring and other purposes, now it is finding more and more place in our lives. We can see the effects of SWS in health, sports, entertainment, education, business and other fileds, especially for the projects of health sector many products are available to the end users. Different SWS that are classified according to its features and methods of use have common features such as ability to make high-capacity wireless communication and housing embedded sensors. When invetigating the studies of SWS that include various forms and numbers of sensors, it is seen that most preferred sensors are; ECG sensor, Glucose sensor, body temperature sensor, blood pressure sensor, SpO(2) sensor and Accelerometer. General details of SWS and leading research projects from past to present are described within the scope of this article